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@ARTICLE{Tshaus:154360,
      author       = {Tüshaus, Johanna and Müller, Stephan A and Kataka, Evans
                      Sioma and Zaucha, Jan and Sebastian Monasor, Laura and Su,
                      Minhui and Güner, Gökhan and Jocher, Georg and Tahirovic,
                      Sabina and Frishman, Dmitrij and Simons, Mikael and
                      Lichtenthaler, Stefan},
      title        = {{A}n optimized quantitative proteomics method establishes
                      the cell type-resolved mouse brain secretome.},
      journal      = {The EMBO journal},
      volume       = {39},
      number       = {20},
      issn         = {1460-2075},
      address      = {Hoboken, NJ [u.a.]},
      publisher    = {Wiley},
      reportid     = {DZNE-2021-00213},
      pages        = {e105693},
      year         = {2020},
      note         = {ISSN 1460-2075 not unique: **3 hits**.},
      abstract     = {To understand how cells communicate in the nervous system,
                      it is essential to define their secretome, which is
                      challenging for primary cells because of large cell numbers
                      being required. Here, we miniaturized secretome analysis by
                      developing the 'high-performance secretome protein
                      enrichment with click sugars' (hiSPECS) method. To
                      demonstrate its broad utility, hiSPECS was used to identify
                      the secretory response of brain slices upon LPS-induced
                      neuroinflammation and to establish the cell type-resolved
                      mouse brain secretome resource using primary astrocytes,
                      microglia, neurons, and oligodendrocytes. This resource
                      allowed mapping the cellular origin of CSF proteins and
                      revealed that an unexpectedly high number of secreted
                      proteins in vitro and in vivo are proteolytically cleaved
                      membrane protein ectodomains. Two examples are neuronally
                      secreted ADAM22 and CD200, which we identified as substrates
                      of the Alzheimer-linked protease BACE1. hiSPECS and the
                      brain secretome resource can be widely exploited to
                      systematically study protein secretion and brain function
                      and to identify cell type-specific biomarkers for CNS
                      diseases.},
      keywords     = {ADAM Proteins: cerebrospinal fluid / ADAM Proteins:
                      metabolism / Amyloid Precursor Protein Secretases:
                      antagonists $\&$ inhibitors / Amyloid Precursor Protein
                      Secretases: cerebrospinal fluid / Amyloid Precursor Protein
                      Secretases: metabolism / Animals / Antigens, CD:
                      cerebrospinal fluid / Antigens, CD: metabolism / Aspartic
                      Acid Endopeptidases: antagonists $\&$ inhibitors / Aspartic
                      Acid Endopeptidases: cerebrospinal fluid / Aspartic Acid
                      Endopeptidases: metabolism / Astrocytes: metabolism / Brain:
                      cytology / Brain: metabolism / Cells, Cultured /
                      Cerebrospinal Fluid Proteins / Chromatography, Liquid / Gene
                      Ontology / Lipopolysaccharides: pharmacology / Mice / Mice,
                      Inbred C57BL / Microglia: metabolism / Nerve Tissue
                      Proteins: cerebrospinal fluid / Nerve Tissue Proteins:
                      metabolism / Neurons: metabolism / Oligodendroglia:
                      metabolism / Principal Component Analysis / Proteome:
                      metabolism / Proteomics: methods / Software / Tandem Mass
                      Spectrometry / CSF (Other) / BACE1 (Other) / brain cells
                      (Other) / proteomics (Other) / secretomics (Other)},
      cin          = {AG Lichtenthaler / AG Haass / AG Tahirovic / AG Simons /
                      LIS},
      ddc          = {570},
      cid          = {I:(DE-2719)1110006 / I:(DE-2719)1110007 /
                      I:(DE-2719)1140003 / I:(DE-2719)1110008 /
                      I:(DE-2719)1040260},
      pnm          = {342 - Disease Mechanisms and Model Systems (POF3-342) / 341
                      - Molecular Signaling (POF3-341)},
      pid          = {G:(DE-HGF)POF3-342 / G:(DE-HGF)POF3-341},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:32954517},
      pmc          = {pmc:PMC7560198},
      doi          = {10.15252/embj.2020105693},
      url          = {https://pub.dzne.de/record/154360},
}